Support vector machines based neuro-fuzzy control of nonlinear systems

摘要: In this work, a novel neuro-fuzzy control structure has been proposed for unknown nonlinear plants, which is referred to as the SVM-based ANFIS controller since it emerged from fusion of adaptive network fuzzy inference system (ANFIS) and support vector machines (SVMs). controller, an obtained SVM model plant used extract gradient information predict future behavior dynamics, are necessary find additive correction term update parameters. The motivation behind use SVMs modeling dynamics fact that algorithms possess higher generalization ability guarantee global minima. simulation results have revealed exhibits considerably high performance by yielding very small transient- steady-state tracking errors can maintain its under noisy conditions.